TITLE:
The Application of Artificial Intelligence-Based Risk Management Models in Financial Markets
AUTHORS:
Sixuan Wang
KEYWORDS:
Artificial Intelligence, Risk Management, Financial Markets, Machine Learning, Deep Learning, Theoretical Research
JOURNAL NAME:
Open Journal of Social Sciences,
Vol.12 No.11,
November
15,
2024
ABSTRACT: Artificial intelligence is reshaping the field of financial risk control, bringing revolutionary changes to risk management. This study systematically explores the application prospects and potential impacts of artificial intelligence (AI)-driven risk management models in financial markets. As the complexity and uncertainty of financial markets increase, AI technologies, especially machine learning and deep learning, are reshaping the field of financial risk control with their powerful data processing and pattern recognition capabilities. The research conducts an in-depth analysis of how AI technology enhances risk identification, assessment, and control capabilities, including processing massive data, capturing complex non-linear relationships, and supporting real-time risk monitoring and dynamic risk adjustment. The article focuses on discussing the theoretical application scenarios of AI in market risk, credit risk, and operational risk management. The study elaborates on the basic framework of neural network-based financial risk management models from a theoretical perspective, including multi-layer neural network structures, model training and optimization strategies, as well as model evaluation and interpretability analysis methods. Meanwhile, the research delves into the main challenges faced by AI models in financial risk control applications, including data quality and privacy protection, model complexity and computational resource requirements, and regulatory compliance and ethical considerations, and proposes possible coping strategies from a theoretical perspective. This study provides an important theoretical basis for understanding and addressing the challenges of financial risk management in the AI era, offers insights for constructing responsible AI risk control systems, and has significant theoretical implications for promoting the deep integration of financial technology and risk management.